基于三维荧光光谱的土壤中石油类有机物分类识别 
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Identification of Petroleum Organic Matter in Soil Based on Three-Dimensional Fluorescence Spectroscopy
1 中国科学院安徽光学精密机械研究所环境光学与技术重点实验室, 安徽 合肥 230031
2 中国科学技术大学, 安徽 合肥 230026
3 中国科学院合肥物质科学研究院安徽省环境光学监测技术重点实验室, 安徽 合肥 230031
4 合肥学院先进制造工程学院, 安徽 合肥 230601
图 & 表
图 1. 0#柴油降噪前后的效果比较。(a)降噪前;(b)降噪后
Fig. 1. Comparison of effects before and after noise reduction of 0# diesel. (a) Before noise reduction; (b) after noise reduction
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图 2. 土壤中6种油的三维荧光光谱信号。(a) 0#柴油;(b)生物柴油;(c) 5w-40型润滑油;(d) 15w-40型润滑油;(e) VN2变速箱机油;(f) 92#汽油
Fig. 2. Three-dimensional fluorescence signals of 6 oils in soil. (a) 0# diesel; (b) biodiesel; (c) 5w-40 lubricating oil; (d) 15w-40 lubricating oil; (e) VN2 gearbox oil; (f) 92# gasoline
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图 3. 土壤中6种油的前三个主成分
Fig. 3. First 3 principal components of 6 oils in soil
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表 16种油指纹区域内的峰值位置坐标
Table1. Coordinates of peak positions in fingerprint areas of 6 oils
| Type of petroleum products | Left area(EX,EM) | Right area(EX,EM) |
|---|
| 0# diesel | (232,334) | (288,334) | | Biodiesel | (230,346) | (276,334) | | 5w-40 lubricating oil | (236,336) | (290,348) | | 11w-40 lubricating oil | (236,346) | (290,344) | | VN2 gearbox oil | (238,346) | (270,372) | | 92# gasoline | (226,338) | (270,336) |
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表 26种样品的三维光谱统计参数
Table2. 3D spectral statistical parameters of 6 samples
| Type of petroleum products | z | σ | (mx ,my ) | ske | kur | ρ | fi |
|---|
| 0# diesel | 55.17 | 127.8 | (257.4,352.7) | 0.6547 | 2.221 | -0.1057 | 3.340 | | 53.87 | 122.0 | (256.9,353.0) | 0.6619 | 2.707 | -0.1624 | 3.107 | | 55.81 | 128.2 | (255.1,353.7) | 0.6095 | 2.077 | -0.1226 | 3.307 | | 54.97 | 130.1 | (259.7,353.9) | 0.6927 | 2.304 | -0.1403 | 2.996 | | Biodiesel | 49.65 | 102.7 | (251.2,347.7) | 0.6605 | 4.803 | -0.0645 | 3.078 | | 48.21 | 107.3 | (248.0,345.1) | 0.7015 | 4.701 | -0.0579 | 3.104 | | 48.77 | 100.6 | (252.1,346.5) | 0.6822 | 4.543 | -0.0533 | 3.093 | | 49.15 | 105.8 | (249.7,345.4) | 0.6431 | 4.933 | -0.0688 | 3.089 | | 5w-40 lubricating oil | 22.85 | 77.73 | (273.4,351.2) | 2.527 | 7.709 | -0.4140 | 4.036 | | 24.63 | 80.98 | (271.6,349.1) | 2.579 | 7.534 | -0.4937 | 4.311 | | 23.57 | 75.20 | (275.8,350.9) | 2.611 | 7.378 | -0.4107 | 4.089 | | 22.13 | 73.31 | (270.6,352.0) | 2.499 | 7.944 | -3.9527 | 4.151 | | 15w-40 lubricating oil | 20.20 | 70.35 | (280.7,353.2) | 2.117 | 9.273 | -0.5840 | 4.288 | | 19.61 | 71.35 | (284.9,352.8) | 1.989 | 10.27 | -0.6347 | 3.864 | | 19.77 | 69.44 | (281.1,353.4) | 2.366 | 8.964 | -0.5238 | 4.291 | | 17.05 | 67.87 | (283.7,353.5) | 2.034 | 9.541 | -0.6049 | 4.850 | | VN2 gearbox oil | 70.88 | 134.4 | (272.6,384.5) | 0.465 | 1.425 | -0.0622 | 2.805 | | 73.58 | 128.6 | (269.6,380.7) | 0.399 | 1.945 | -0.1037 | 2.143 | | 67.42 | 139.7 | (270.1,386.2) | 0.507 | 1.843 | -0.0894 | 3.027 | | 69.83 | 133.1 | (273.4,380.5) | 0.473 | 2.157 | -0.0576 | 3.101 | | 92# gasoline | 9.233 | 31.15 | (254.1,334.8) | 2.008 | 9.080 | -0.1251 | 3.584 | | 10.35 | 34.23 | (252.4,334.2) | 2.105 | 7.671 | -0.2089 | 4.647 | | 8.181 | 33.75 | (251.3,333.6) | 2.360 | 10.45 | -0.1114 | 5.252 | | 8.293 | 29.82 | (255.6,337.3) | 2.032 | 9.197 | -0.2139 | 3.374 |
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表 3前3种主成分的累计贡献率
Table3. Cumulative contribution rates of first 3 principal components
| Principal component | Contribution rate /% | Cumulative contribution rate /% |
|---|
| PC1 | 45.34 | 45.34 | | PC2 | 26.16 | 71.50 | | PC3 | 17.29 | 88.79 |
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表 4前3种主成分的得分矩阵
Table4. Score matrices of first 3 principal components
| Principal component | z | σ | mx | my | ske | kur | ρ | fi |
|---|
| PC1 | 0.708 | 0.897 | -0.204 | 0.302 | -0.821 | -0.772 | 0.219 | -0.391 | | PC2 | 0.114 | 0.221 | 0.710 | 0.622 | 0.179 | -0.056 | -0.282 | 0.258 | | PC3 | -0.066 | -0.135 | 0.272 | 0.153 | -0.085 | 0.228 | 0.888 | 0.179 |
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表 5BP-ANN分类结果
Table5. Classification results of BP-ANN
| Type of petroleum products | 0# diesel | Biodiesel | 5w-40 lubricating oil | 15w-40 lubricating oil | Gearbox oil | 92# gasoline |
|---|
| Amount of samples | 30 | 30 | 30 | 30 | 30 | 30 | | Identify the correct amount | 29 | 29 | 26 | 28 | 30 | 30 | | Correct rate /% | 96.7 | 96.7 | 86.7 | 93.3 | 100 | 100 | | Average correct rate /% | 95.6 |
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左兆陆, 赵南京, 孟德硕, 黄尧, 殷高方, 刘建国, 谷艳红. 基于三维荧光光谱的土壤中石油类有机物分类识别[J]. 激光与光电子学进展, 2019, 56(22): 222601. Zhaolu Zuo, Nanjing Zhao, Deshuo Meng, Yao Huang, Gaofang Yin, Jianguo Liu, Yanhong Gu. Identification of Petroleum Organic Matter in Soil Based on Three-Dimensional Fluorescence Spectroscopy[J]. Laser & Optoelectronics Progress, 2019, 56(22): 222601.
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